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CES 2018 VRAR

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This slide is my observation of VRAR technology and market with my visiting in CES 2018. Although the VR market has been going up and down in past three years, market leaders (like Vive or so) are still pushing the product spec toward better experience (finer resolution and wireless), and start-up companies are focusing on innovative tracking solutions for whole-body and fingers. Hope this slide helps those who are interested in the VR tech development.

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CES 2018 VRAR

  1. 1. CES 2018 VRAR jAMES Wang Jan. 2018
  2. 2. Content • CES Innov. Awards (2016-2018) • Misc VR Sys & Appl. • Body & Finger Tracking Solutions • Location-based VR Sys & Solutions
  3. 3. CES 2018 VRAR Brief • No big surprise in VR booths, most companies are currently pursuing 1. Better spec & feature: higher resolution, wireless 2. Standalone HMD with: inside-out tracking & 6DoF controller 3. Tracking more DoFs: whole-body, fingers … not matured so far • Really fun VR game usually is the one with customized HWs • More smart-glasses than real AR
  4. 4. CES Innov. Awards (about ARVR)
  5. 5. Wearable 2016 2017 Innov. awards began to go to VR products
  6. 6. 2017 – Virtual Reality Many talking about 360°videos …
  7. 7. 2018 – VR&AR AR head set and standalone VR coming in …
  8. 8. Misc VR Sys & Appl.
  9. 9. Vive Pro • Dual-Cam not ready for developers • Wireless: Intel WiGig 60GHz => Good UX • 70% resolution increase reduces “screen-door” effect
  10. 10. Vive Pro
  11. 11. Vive Pro Backpack Solution Wirelss Solution • HP Z VR backpack • Core i7 • nVIDIA Quadro P5200 • 4.6kG & appor. 1-Hr • $3,300 • It seems that VIVE is thinking what’s the best solution for un- tethered gaming scenario !?
  12. 12. LUCI - immers • Target: high-quality immerse video experience • 4K TV/movies • Dual 1920x1080 • Weight: 185g => very light-weight and comfortable
  13. 13. LUCI-alyx vs. Pimax-8K 8K War & Dream
  14. 14. LUCI-alyx vs. Pimax-8K Before shipment, ideas are just ideas ~~~
  15. 15. Pico goblin • The first company to announce a standalone VR set with 6DoF head & 6DoF controller tracking • Need offset calibration sometimes • Jitter, inaccurate, translation happens when being rotated • Controller tracking actually … sucks
  16. 16. Misc AR Sys & Appl.
  17. 17. AR Wear • A lot of smart-glasses • None of them are MagicLeap styled eyewears ^^
  18. 18. MERGE • Very creative & interesting AR toy for kids • AR toy: markered cube + App + or goggle • Very educational for kids • 6DoF Blaster
  19. 19. Body & Finger Tracking Solutions
  20. 20. ORBBEC • 19-joint depth-based tracking • Like Kinect but with 6DoF pose of each joint • Coarse tracking, it seems not bad => but its bulky size only suitable for TV video game • Not an accurate tracking that's needed by VR
  21. 21. Xsens • IMU-based tracking of quaternions • Whole-body tracking: 22 joints • => 10-finger tracking not yet ready • Need initial pose calibration • 1% drift for not so long time • Best solution may be: optical + IMUs
  22. 22. VRFREE - Sensoryx • HMD to glove => optical • Finger to glove => 2x5 (finger) x2 (hand) = 20 IMU modules; 950MHz wireless communication • Cannot cross fingers, Not good enough • Significant latency (especially trying to flip balls by both hands) … not sure due to wireless or filtering optical IMUs
  23. 23. uSense • Target: mobile application for head & hand tracking • Obvious jitter and may lost tracking when ten fingers crossed
  24. 24. ManoMotion • Real-time 3D gesture analysis with RGB input, running on smartphone • Product: SDK for Android/iOS • One hand only so far • Finger tracking not good so far
  25. 25. BeBop • Finger sensing with fabric piezoresistivity • Haptic feedback (by vibrator) not bad • Sometimes lost tracking due to mismatch between glove and fingers • Only 1-DoF for each finger
  26. 26. BeBop • Piezoresistive material can be used for detecting misc motions, but may not be accurate
  27. 27. GoTouchVR • A France-based company • Camera-based finger tracking (from Leap Motion) • Neural-science based haptic feedback (ultrasonic vibration) … based on a lot of research papers
  28. 28. Location-based VR Sys & Solutions
  29. 29. YAW • Currently a Kickstarter project • A rotational motion simulator, suitable for home entertainment • Compatible with Simtools, on PC platform most of the VR games can control it • Max loading: 150 (kg)
  30. 30. ICAROS • A Germany-based company • Product: H/W + SDK (rotation output) • 2-axis gimbal for human body (no motors used, rotated by human body mass shifting) • Latency between gimbal rotation output and graphics rendering => caused nausea abit • More like exercise + entertainment => practice core-muscle => good for gym
  31. 31. REALIS • SZ-based company with biz model to provide total solution for location-based stores • light-ball based => there is chance to hit & break the ball supporter • 10x10 (m^2) requires 2x4 camera at least (in CES they used 4x4 cameras to ensure reliability) • A little inaccurate and laggy
  32. 32. REALIS Optotrack-like tracking
  33. 33. Voxel • Location-based facility • Kinet-like body optical tracking • Cave-like image projection
  34. 34. Hologate Vive controller inside Vive-based total solution of multiple users shooting game for location-based stores
  35. 35. Hologate • Vive-based, tethered HMD to i) restrict locomotion ii) to release wire inconvenience • Well designed for multiple users in shooting game: players are separated by game design and real space, although cannot run too far • Gun is made directly with Vive controller • Link: http://hologate.com/about/
  36. 36. WePlay • The best experience of one-player VR game
  37. 37. WePlay • The best experienced game for one-player VR game
  38. 38. Modal VR • Founded by Nolan Bushnell (founder of Atari) • Head tracking: • Position tracking (GPS-principle) + • Orientation tracking (IMU) • Tracking range: sqrt(9e5ft^2/(3.3^2)) = 287m => 3-football filed wide • 10-ms latency for each Rx, N Rxs causes 10xN ms latency • Experience: not good enough • HMD getting loosen when running • Feel dizzy when head rotates
  39. 39. Modal VR • Tracking range: sqrt(9e5ft^2/(3.3^2)) = 287m => 3-football filed wide • 10-ms latency for each Rx => N Rxs causes 10xN ms latency
  40. 40. James D.B. Wang • Background: • Career Focus: • Expert in Motion Tracking & Machine Learning • Expertise: • IMU-based motion algorithm development in wearables and VR/AR • Machine learning for real-time human motion recognition • Sensor design (microphone, accelerometer, angular rate sensor) • System integration modeling, analysis and design optimization

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